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pdfBehavioral Risk Factor Surveillance System
OVERVIEW: BRFSS 2015
July 2016
Background
The Behavioral Risk Factor Surveillance System (BRFSS) is a collaborative project between all of the states in
the United States (US) and participating US territories and the Centers for Disease Control and Prevention (CDC).
The BRFSS is administered and supported by CDC's Population Health Surveillance Branch, under the Division
of Population Health at the National Center for Chronic Disease Prevention and Health Promotion. The BRFSS
is an ongoing surveillance system designed to measure behavioral risk factors for the noninstitutionalized adult
population (aged 18 years of age and older) residing in the United States. The BRFSS was initiated in 1984,
with 15 states collecting surveillance data on risk behaviors through monthly telephone interviews. Over time,
the number of states participating in the survey increased, and by 2001, 50 states, the District of Columbia,
Puerto Rico, Guam, and the US Virgin Islands were participating in the BRFSS. Today, all 50 states, the
District of Columbia, Puerto Rico, and Guam collect data annually; American Samoa, the Federated States of
Micronesia, and Palau collect survey data over a limited point-in-time (usually 1 to 3 months). In this document,
the term state is used to refer to all areas participating in the BRFSS, including the District of Columbia, Guam,
and the Commonwealth of Puerto Rico.
The BRFSS objective is to collect uniform, state-specific data on preventive health practices and risk
behaviors that are linked to chronic diseases, injuries, and preventable infectious diseases that affect the
adult population. Factors assessed by the BRFSS in 2015 include tobacco use, HIV/AIDS knowledge and
prevention, exercise, immunization, health status, healthy days health-related quality of life, health care access,
hypertension awareness, arthritis burden, chronic health conditions, alcohol consumption, fruits and vegetables,
and seatbelt use. Since 2011, the BRFSS conducts both landline telephone- and cellular telephone-based
surveys. In conducting the BRFSS landline telephone survey, interviewers collect data from a randomly
selected adult in a household. In conducting the cellular telephone version of the BRFSS questionnaire,
interviewers collect data from an adult who participates by using a cellular telephone and resides in a private
residence or college housing.
The BRFSS field operations are managed by state health departments that follow protocols adopted by the
states, with technical assistance provided by CDC. State health departments collaborate during survey
development and conduct the interviews themselves or use contractors. The data are transmitted to CDC for
editing, processing, weighting, and analysis. An edited and weighted data file is provided to each participating
health department for each year of data collection, and summary reports of state-specific data are prepared by
CDC. Health departments use the data for a variety of purposes, including identifying demographic variations in
health-related behaviors, targeting services, addressing emergent and critical health issues, proposing legislation
for health initiatives, and measuring progress toward state health objectives.1 For specific examples of how state
officials use the finalized BRFSS data sets, please refer to the appropriate state information on the BRFSS
website.
Health characteristics estimated from the BRFSS pertain to the noninstitutionalized adult population—aged 18
years or older—who reside in the United States. In 2015, an optional module was included to provide a measure
for several childhood health and wellness indicators, including asthma prevalence for people aged 17 years or
younger.
As previously noted, respondents are identified through telephone-based methods. According to the 2014
American Community Survey (ACS), 97.6% of all occupied housing units in the United States had telephone
service available and telephone noncoverage ranged from 1.5% in Connecticut and New Jersey to 3.5% in
Nevada. It is estimated that 5.7% of occupied households in Puerto Rico did not have telephone service.2 The
increasing percentage of households that are abandoning their landline telephones for cellular telephones has
significantly eroded the population coverage provided by landline telephone-based surveys to pre-1970s levels.
The preliminary results from the National Health Interview Survey (NHIS) show that the number of American
households with only wireless telephones continued to increase in 2015. For the second half of 2015, the
percentage of cellular telephone-only households was 48.3 percent.3 In households where both landline
telephone and wireless telephone service are available, there is a trend toward increased use of wireless
communication.3 Beginning in 2014, all adults contacted through their personal (nonbusiness) phone numbers
were eligible regardless of their landline phone use (i.e., complete overlap).
No direct method of accounting for non-telephone coverage is employed by the BRFSS. Continuing a weighting
method first introduced in 2011, the BRFSS used iterative proportional fitting (or raking) to weight the data.
Raking adjusts the data so that groups underrepresented in the sample can be more accurately represented in the
final data set. Raking allows for the incorporation of cellular telephone survey data; it permits the introduction
of additional demographic characteristics and more accurately matches sample distributions to known
demographic characteristics of populations, as compared with the pre-2011 BRFSS weighting methods. The use
of raking has been shown by researchers to reduce error within estimates.4 The BRFSS raking includes
categories of age by gender, detailed race and ethnicity groups, education levels, marital status, regions within
states, gender by race and ethnicity, telephone source, renter or owner status, and age groups by race and
ethnicity. In 2015, 50 states, the District of Columbia, Guam, and Puerto Rico collected samples of interviews
conducted both by landline telephone and cellular telephone.
The BRFSS Design
The BRFSS Questionnaire
Each year, the states—represented by their BRFSS coordinators and CDC—agree on the content of the
questionnaire. The BRFSS questionnaire consists of a core component and optional modules. Many questions
are taken from established national surveys, such as the National Health Interview Survey or the National
Health and Nutrition Examination Survey. This practice allows the BRFSS to take advantage of questions that
have been tested and allows states to compare their data with those from other surveys. Any new questions that
states, federal agencies, or other entities propose as additions to the BRFSS must go through cognitive testing
and field testing before they can become part of the BRFSS questionnaire. In addition, a majority vote of all
state representatives is required before questions are adopted. The BRFSS guidelines—agreed upon by the state
representatives and CDC—specify that all states ask the core component questions without modification. They
may choose to add any, all, or none of the optional modules and may add questions of their choosing at the end
of the questionnaire (state-added questions).
The questionnaire has three parts
1. Core component: A standard set of questions that all states use. Core content includes queries about current
health-related perceptions, conditions, and behaviors (e.g., health status, health care access, alcohol
consumption, tobacco use, fruit and vegetable consumption, and HIV/AIDS risks), as well as demographic
questions. The core component includes the annual core comprising questions asked each year, and rotating
core questions that are included in even- and odd–numbered years.
2. Optional BRFSS modules: Sets of questions on specific topics (e.g., excess sun exposure, cancer
survivorship, mental illness, stigma) that states elect to use on their questionnaires. In 2015, the BRFSS
supported 25 optional modules. Generally, CDC programs submit module questions and the states vote to adopt
final questions that can be included as optional modules. For more information, please see the questionnaire
section of the BRFSS website.
3. State-added questions: Individual states develop or acquire these questions and add them to their BRFSS
questionnaires. CDC neither edits nor evaluates these questions.
The BRFSS supported 25 modules in 2015, but states limited modules and added questions to only the most
useful for their state program purposes, in order to keep surveys at a reasonable length. Because different states
have different needs, there is wide variation between states in terms of question totals each year. The BRFSS
implements a new questionnaire in January and usually does not change it significantly for the rest of the year.
The flexibility of state-added questions, however, does permit additions, changes, and deletions at any time
during the year.
The 2015 list of optional modules used on both the landline telephone and cellular telephone surveys is
available on the BRFSS website. In order to allow for a wider range of questions in optional modules, combined
landline telephone and cellular telephone data for 2015 include up to three split versions of the questionnaire. A
split version is when a subset of telephone numbers for data collection still followed the state sample design,
and administrators used it as the state’s BRFSS sample, but the optional modules and state-added questions may
have been different from other split version questionnaires. For additional information on split version
questionnaires see the 2015 module data appendix table.
Annual Questionnaire Development
The governance of the BRFSS includes a representative body of state health officials, elected by region. During
the year, the State BRFSS Coordinators Working Group meets with CDC’s BRFSS program management. One
task of this group is to develop a 5-year, long-term plan for the BRFSS core instrument. The 2015 BRFSS
questionnaire represents the fourth year of a 5-year plan (2012-2016).
Before the beginning of the calendar year, CDC provides states with the text of the core component and the
optional modules that the BRFSS will support in the coming year. States select their optional modules and ready
any state-added questions they plan to use. Each state then constructs its own questionnaire. The order of the
questioning is always the same—interviewers ask questions from the core component first, then they ask any
questions from the optional modules, and the state-added questions. This content order ensures comparability
across states and follows the BRFSS guidelines. Generally, the only changes that the standard protocol allows
are limited insertions of state-added questions on topics related to core questions. CDC and state partners must
agree to these exceptions. In some cases, however, states have not been able to follow all set guidelines. Users
should refer to the Comparability of Data document, which lists the known deviations.
Once each state finalizes its questionnaire content—consisting of the core questionnaire, optional modules, and
state-added questions--the state prepares a hard copy or electronic version of the instrument and sends it to
CDC. States use the questionnaire without changes for one calendar year, and CDC archives a copy on the
BRFSS website. If a significant portion of any state’s population does not speak English, states have the option
of translating the questionnaire into other languages. Currently, CDC provides a Spanish version of the core
questionnaire and optional modules. Specific wording of the Spanish version of the questionnaire may be
adapted by the states to fit the needs of their Hispanic populations.
Sample Description
In a telephone survey such as the BRFSS, a sample record is one telephone number in the list of all telephone
numbers the system randomly selects for dialing. To meet the BRFSS standard for the participating states'
sample designs, one must be able to justify sample records as a probability sample of all households with
telephones in the state. All participating areas met this criterion in 2015. Fifty-one projects used a
disproportionate stratified sample (DSS) design for their landline samples. Guam and Puerto Rico used a simple
random-sample design.
In the type of DSS design that states most commonly used in the BRFSS landline telephone sampling, the
BRFSS divides telephone numbers into two groups, or strata, which are sampled separately. The high-density
and medium-density strata contain telephone numbers that are expected to belong mostly to households.
Whether a telephone number goes into the high-density or medium-density stratum is determined by the number
of listed household numbers in its hundred block, or set of 100 telephone numbers with the same area code,
prefix, and first 2 digits of the suffix and all possible combinations of the last 2 digits. BRFSS puts numbers
from hundred blocks with 1 or more listed household numbers (1+ blocks, or banks) in either the high-density
stratum (listed 1+ blocks) or medium-density stratum (unlisted 1 + blocks). The BRFSS samples the two strata
to obtain a probability sample of all households with telephones.
Cellular telephone sampling frames are commercially available and the system can call random samples of
cellular telephone numbers, but doing so requires specific protocols. The basis of the 2015 BRFSS sampling
frame is the Telecordia database of telephone exchanges (e.g., 617-492-0000 to 617-492-9999) and 1,000 banks
(e.g., 617-492-0000 to 617-492-0999). The vendor uses dedicated cellular 1,000 banks, sorted on the basis of
area code and exchange within a state. The BRFSS forms an interval—K—by dividing the population count of
telephone numbers in the frame—N—by the desired sample size— n. The BRFSS divides the frame of
telephone numbers into n intervals of size K telephone numbers. From each interval, the BRFSS draws one 10
digit telephone number at random.
The target population (aged 18 years and older) for cellular telephone samples in 2015 consists of people
residing in a private residence or college housing who have a working cellular telephone.
In the sample design, each state begins with a single stratum. To provide adequate sample sizes for smaller
geographically defined populations of interest, however, many states sample disproportionately from strata that
correspond to substate regions. In 2015, the 46 states or territories with disproportionately sampled geographic
strata were Alabama, Alaska, Arizona, Arkansas, California, Colorado, Connecticut, Delaware, Georgia,
Hawaii, Idaho, Illinois, Indiana, Iowa, Kansas, Kentucky, Louisiana, Maine, Maryland, Massachusetts,
Michigan, Minnesota, Mississippi, Missouri, Montana, Nebraska, Nevada, New Hampshire, New Jersey, New
Mexico, New York, North Carolina, Ohio, Oklahoma, Pennsylvania, Puerto Rico, Rhode Island, South
Carolina, South Dakota, Tennessee, Texas, Utah, Vermont, Virginia, Washington, and Wisconsin. As a
precaution to protect the confidential responses provided by the respondent, specific variables (such as substate
geographic identifiers, detailed race or ethnicity, and older than 80 years of age) in a given year are removed.
State health departments may directly collect data from their states or they may use a contractor. In 2015, 9 state
health departments collected their data in-house and the remainder contracted with other data collectors. In
2015, the CDC provided samples purchased from Marketing Systems Group, Inc. (MSG) to all 53 states and
territories.
Data Collection
Interviewing Procedures
In 2015, 53 states or territories used Computer-Assisted Telephone Interview (CATI) systems. CDC supports
CATI programming using the Ci3 WinCATI software package. This support includes programming the core
and module questions for data collectors, providing questionnaire scripting of state-added questions for states
requiring such assistance, and contracting with a Ci3 consultant to assist states. Following guidelines provided
by the BRFSS, state health personnel or contractors conduct interviews. The core portion of the questionnaire
lasts an average of 18 minutes. Interview time for modules and state-added questions is dependent upon the
number of questions used, but generally, they add 5 to 10 minutes to the interview.
Interviewer retention is very high among states that conduct the survey in-house. The state coordinator or
interviewer supervisor conducts repeated training specific to the BRFSS. Contractors typically use interviewers
who have experience conducting telephone surveys, but these interviewers are given additional training on the
BRFSS questionnaire and procedures before they are approved to work on the BRFSS.
The BRFSS protocols require evaluation of interviewer performance. In 2015, all BRFSS surveillance sites had
the capability to monitor their interviewers. Interviewer-monitoring systems vary from listening to the
interviewer only at an on-site location to listening to both the interviewer and respondent at remote locations.
Some states also use verification callbacks in addition to direct monitoring. Contractors typically conducted
systematic monitoring of each interviewer a certain amount of time each month. All states had the capability to
tabulate disposition code frequencies by interviewer. These data were the primary means for quantifying
interviewer performance.
States conducted telephone interviews during each calendar month. They made calls 7 days per week, during
both daytime and evening hours. They followed standard BRFSS procedures for rotation of calls over days of
the week and time of day. Detailed information on interview response rates is available in the BRFSS 2015
Summary Data Quality Report.
Data Processing
Preparing for Data Collection and Data Processing
Data processing is an integral part of any survey. Because states collect and submit data to CDC each month,
the BRFSS performs routine data processing tasks on an ongoing basis. Once the final version of the new
questionnaire becomes available each year, CDC staff take steps to prepare for the next cycles of data
collection. These steps include developing edit specifications, programming portions of the Ci3 WinCATI
software, programming the editing software, and producing telephone sample estimates as requested by states
and ordering the sample from the contract vendor. CDC produces a Ci3 WinCATI data entry module for each
state that requests it. CDC staff also must incorporate skip patterns, together with some consistency edits, and
response-code range checks into the CATI system. These edits and skip patterns serve to reduce interviewer,
data entry, and skip errors. Developers prepare data conversion tables that help processors read the survey data
from the entry module, call information from the sample tracking module, and combine information into the
final format for that data year. CDC also creates and distributes a Windows-based editing program that can
perform data validations on files with proper survey result formats. This program helps users with output lists of
errors or warns users about conditions of concern that may exist in the data.
CDC begins to process data for the survey year as soon as states or their contractors begin submitting data to the
data management mailbox. Data processing continues throughout the survey year. CDC receives and tracks
monthly data submissions from the states. Once data are received from a state, CDC staff run editing programs
and cumulative data quality checks and note any problems in the files. A CDC programmer works with each
state until any problems are optimally resolved. CDC staff generate data quality reports and share them with
state coordinators, who review the reports and discuss any potential problems. Once CDC receives and validates
the entire year of data for a state, processors run several year-end programs on the data. These programs
perform some additional, limited data cleanup and fixes specific to each state and data year and produce reports
that identify potential analytic problems with the data set. Once this step is completed, data are ready for
assigning weights and adding calculated variables. Calculated variables are created for the benefit of users and
can be noted in the data set by the leading underscore in the variable name. The following calculated variables
are examples of results from this procedure:
•
•
•
_RFSMOK3.
_HCVU651.
_AGE80.
•
_TOTINDA.
For more information, see the Calculated Variables and Risk Factors in Data Files document. Several variables
from the data file are used to create these variables in a process that varies in complexity. Some are based only
on combined codes, while others require sorting and combining of particular codes from multiple variables.
Almost every variable derived from the BRFSS interview has a code category labeled refused and assigned
values of 9, 99, or 999. These values may also be used to represent missing responses. Missing responses may
be due to non-interviews (a non-interview response results when an interview ends prior to this question and an
interviewer codes the remaining responses as refused) and missing responses due to skip patterns in the
questionnaire. This code, however, may capture some questions that were supposed to have answers, but for
some reason do not have them, and appeared as a blank or another symbol. Combining these types of responses
into a single code requires vigilance on the part of data file users who wish to separate (1) results of respondents
who did not receive a particular question and (2) results from respondents who, after receiving the question,
gave an unclear answer or refused to answer it.
Weighting the Data
When data are unweighted, each record counts the same as any other record. Unweighted data analyses make
the assumption that each record has an equal probability of being selected and that noncoverage and
nonresponse are equal among all segments of the population. When deviations from these assumptions are large
enough to affect the results from a data set, weighting each record appropriately can help to adjust for
assumption violations. In the BRFSS, such weighting serves as a blanket adjustment for noncoverage and
nonresponse and forces the total number of cases to equal population estimates for each geographic region,
which for the BRFSS sums to the state population. Regardless of state sample design, use of the final weight in
analysis is necessary if users are to make generalizations from the sample to the population.
Following is a general description of the 2015 BRFSS weighting process. Where a factor does not apply,
processors set its value to one for calculation. In order to reduce bias due to unequal probability of selection,
design weighting is conducted. The BRFSS also uses iterative proportional fitting, or raking, to adjust for
demographic differences between those persons who are sampled and the population that they represent. The
weighting methodology, therefore, comprises two sections—design weight and raking.
Design weights are calculated using the weight of each geographic stratum (_STRWT), the number of landline
phones within a household (NUMPHON2), and the number of adults who use those phones (NUMADULT).
For cellphone respondents, both NUMPHON2 and NUMADULT are set to 1. The formula for the design
weight is
Design Weight = _STRWT * (1/NUMPHON2) * NUMADULT
In 2015, the inclusion of cellular telephone respondents who also have landline telephones in their household
required an adjustment to the design weights to account for the overlapping sample frames. From each of the
two sample frames, a compositing factor was calculated for the cellular telephone dual sampling frame users.
The BRFSS multiplied the design weight by the compositing factor to generate a composite weight for the
records in the overlapping sample frames. The BRFSS then truncated the design weight based on quartiles
within geographic region, which processors used as the raking input weight.
The stratum weight (_STRWT) accounts for differences in the probability of selection among strata (subsets of
area code or prefix combinations). It is the inverse of the sampling fraction of each stratum. There is rarely a
complete correspondence between strata, defined by subsets of area code or prefix combinations, and regions,
defined by the boundaries of government entities.
BRFSS calculates the stratum weight (_STRWT) using the following items
• Number of available records (NRECSTR) and the number of records users select (NRECSEL)
within each geographic strata and density strata.
• Geographic strata (GEOSTR), which may be the entire state or a geographic subset (e.g.,
counties, census tracts).
• Density strata (_DENSTR) indicating the density of the phone numbers for a given block of
numbers as listed or not listed.
Within each _GEOSTR*_DENSTR combination, BRFSS calculates the stratum weight (_STRWT) from the
average of the NRECSTR and the sum of all sample records used to produce the NRECSEL. The stratum
weight is equal to NRECSTR/NRECSEL.
1/ NUMPHON2
The inverse of the number of residential telephone numbers in the respondent’s
household.
NUMADULT
The number of adults aged 18 years and older in the respondent’s household.
FINAL WEIGHT
The BRFSS rakes the design weight to 8 margins (gender by age group, race or
ethnicity, education, marital status, tenure, gender by race or ethnicity, age group
by race or ethnicity, phone ownership). If the BRFSS includes geographic
regions, it includes 4 additional margins (region, region by age group, region by
gender, region by race or ethnicity). If at least 1 county has 500 or more
respondents, the BRFSS includes 4 additional margins (county, county by age
group, county by gender, county by race or ethnicity).
_LLCPWT
The final weight assigned to each respondent.
The BRFSS uses weight trimming to increase the value of extremely low weights and decrease the value of
extremely high weights. The objective of weight trimming is to reduce errors in the outcome estimates caused
by unusually high or low weights in some categories.
The population estimates obtained for building the target totals are from similar sources used in previous years.
Intercensal population estimates were purchased from The Nielsen Company, LLC, at the county-level for age,
race or ethnicity, and gender. These population estimates are used as the population totals for a state across all
margins. The 5-year year American Community Survey PUMS dataset (2010-2014) was used to obtain
estimates for margins 3, 4, and 5 (education, marital status, tenure). The noninstitutionalized adults were
weighted by the person-level weights to generate the population estimates. The percentages were then used in
the raking margins. The telephone ownership estimates for margin 8 were taken from the state wireless estimate
percentages produced by NCHS and released in February, 2016.
Calculation of a Child Weight
The BRFSS calculates the design weight for child weighting from the stratum weight times the inverse of the
number of telephones in the household and then multiplies by the number of children
Child Design Weight = _STRWT * (1/NUMPHON2) * CHILDREN
CHIILDWT = BRFSS rakes the child design weight to 5 margins including age by gender, race or
ethnicity, gender by race or ethnicity, age by race or ethnicity, and phone ownership.
_CLLCPWT is the weight assigned for each child interview.
References
1.
2.
3.
4.
Remington PL, Smith MY, Williamson DF, Anda RF, Gentry EM, Hogelin GC. Design, characteristics, and
usefulness of state-based behavioral risk factor surveillance: 1981-87. Public health reports (Washington, D.C. :
1974). 1988;103(4):366-375.
Commision FC. Universal Service Monitoring Report. 2015; https://apps.fcc.gov/edocs_public/attachmatch/DOC
337019A1.pdf.
Blumberg SJ, Luke JV. Wireless Substitution: Early Release of Estimates From the National Health Interview
Survey, July–December 2015. 2015; http://www.cdc.gov/nchs/data/nhis/earlyrelease/wireless201605.pdf.
Accessed June, 2016.
Battaglia MP, Frankel MR, Link MW. Improving standard poststratification techniques for random-digit-dialing
telephone surveys. Survey Res Methods 2008;2(1):11-19
File Type | application/pdf |
File Title | Behavioral Risk Factor Surveillance System Overview 2015 |
Subject | BRFSS Behavioral Risk Factor Surveillance System overview 2015 |
Author | CDC |
File Modified | 2016-08-25 |
File Created | 2016-08-18 |